In recent years, major improvements have been made in the area of assistive hearing devices such as hearing aids, consumer headsets and hearables. However, the sound quality has been identified as one of the limiting factors for the end-user acceptance [1]}, [2]}. In order to improve the sound quality, sound pressure equalization algorithms can be used that aim at perceptually restoring the open-ear characteristics when a hearing device is used, typically referred to as acoustic transparency. To achieve acoustic transparency, different approaches can be used [3]}, [4]}, [5]}, [6]}, [7]}, [8]}. Most of these approaches rely on the availability of all acoustic transfer functions between the source(s), the hearing device and the individual eardrum to compute the equalization filter. Thus, an understanding of the impact of different estimations of the required acoustic transfer functions is essential for the practical application of individualized sound pressure equalization.
